فهرست مطالب

  • Volume:5 Issue: 3, 2020
  • تاریخ انتشار: 1399/04/16
  • تعداد عناوین: 8
|
  • Saeed Shirazi, Hamed Baziyad, Naser Ahmadi, Amir Albadvi* Pages 183-193
    Background and aim

    Recently, the use of data science techniques in healthcare has been increased remarkably. Community detection as one the important methods of data science is utilized in the health domain.

    Methods

    This paper detects disease areas based on combination of big data and graph mining methods on drug prescriptions. At first, network of prescription is designed, and Louvain algorithm is applied for community detection of 50000 Iranian prescriptions in 2014 gathered from the Iranian Health Insurance Organization. We use modularity metric for validation of the results and the experts’ opinion as the external validation of communities.

    Results

    The outputs are consist of six communities. These communities are labeled based on experts’ opinion that present the disease fields.

    Conclusion

    The Louvain algorithm has the ability to detect the major communities of the prescription database with an acceptable accuracy. We have proven that these communities present the disease fields.

    Keywords: Big data, Graph theory, Community detection, Drug prescription
  • Elham Nazari, Elias Ameli, Hamed Tabesh* Pages 194-203
    Background & Aim

    Today, with the advent of technology, due to the growing data in the field of health care, it is difficult to manage and analyze this type of data known as the Big Data. This analysis has many capabilities to improve the quality of care, reduce errors and reduce costs in care services.

    Methods

    This study is based on search of databases (PubMed, Google Scholar, Science
    Direct, and Scopus). This investigation has done with the websites and the specialized books with standard key words. After a careful study, 50 sources were in the final article.

    Results

    Since the Big Data Analysis in the field of health has been growing and also
    considered in recent years, this survey identified the necessity of these analyses, the definition of the Big Data, the benefits, resources, architecture, applications, analysis, platforms, Examples and challenges in the field of health care.

    Conclusions

    Familiarity with the big data concepts in the field of healthcare can help researchers in conducting applied research and thus improve the quality of health care services and reduce costs.

    Keywords: Big data, Healthcare, Datamining
  • Yousef Alimohamadi, Firooz Esmaeilzadeh, Parisa Jalali, Mohsen Mohammadi, Mojtaba Sepandi* Pages 204-209
    Introduction

    Timely Detection of outbreaks of infectious diseases can have a very important role in
    surveillance systems. the presence of appropriate methods can have a very important role for this purpose, the aim of the current study was to Evaluation The Performance of Exponentially Weighted Moving Average in the detection of cholera outbreaks using the reported cholera outbreaks in literature.

    Methods

    In the current study the EWMA method was evaluated. To assess the performance of the mentioned methods the six real outbreaks algorithm reported in the literature were used. These reported outbreaks were the daily counts of cholera cases in different countries. After insertion of each outbreak, 7 days inserted as nonoutbreaks days. All analyses performed by MedCalc18.11, Stata version15 and excel 2010.

    Results

    the sensitivity of EWMA was 56.4% (95% CI: 54.3%- 58.5%). The highest sensitivity for outbreak detection was seen in EWMA1 79.18(73.56-84.09) and the lowest was seen in EWMA4 12.2(8.4-17.0). EWMA2 with λ= 0.2 had the best performance with sensitivity 69.8 (63.6-75.5) and specificity 91.4(76.9-98.2) and AUC= 0.80.

    Conclusion

    The EWMA method can be very useful in the detection of outbreaks, but the use of this method along the other models may increase the sensitivity of outbreaks detection.

    Keywords: EWMA, Sensitivity, Specificity, Outbreak
  • Hamed Baziyad*, Saeed Shirazi, Seyed mohammadreza Hosseini, Rasoul Norouzi Pages 210-215
    Background and Aim

    The existence of an intellectual structure for every field is essential for managers and scholars. Intellectual structures provide a comprehensive map of knowledge that can guide researchers and managers to have a better view of their fields. Besides, with high-speed and massive amounts of data and information generation, reading and surveying of all resources are severely tricky. Intellectual maps solve this problem and make a situation for control and monitoring this voluminous and high-speed generated data. Epidemiology is regarded as one of the exciting fields which many researchers focused on it. A study of the structure and criteria of different epidemiological fields has not been done yet. Indeed, there is no serious effort for knowledge discovery of hidden information on epidemiological texts.

    Methods

    In this paper, in order to survey this field, an intellectual structure is provided using co-word analysis. Utilizing co-word analysis discloses relationships and structure among research subjects and topics in a field.

    Results

    Finally, four main clusters were determined, namely: genetic (with 30.53% of surveyed papers), illness (29.47%), modeling (23.16%), and prevention (16.84%).

    Conclusion

    According to epidemiology co-word network, epidemiology area has not been studied from enough different areas, especially from novel technologies

    Keywords: Intellectual structure of epidemiology, Co-word analysis, Text mining, Graph mining, Social network analysis
  • Elham Nazari, MohammadHasan Shahriari, Maryam Edalati Khodabandeh, Hamed Tabesh* Pages 216-225

    One of the challenges of multidisciplinary disciplines such as Medical Informatics, Health Information Technology, etc., especially for those who have just begun research in this field, is the lack of familiarity with some of the key terms and applications of software concepts, including frameworks. Worksheets are widely used in the field of health care and have produced valuable results. Considering the framework advantages in health care sector among designing and estimating the systems in standard ways and comparing the systems in principle for identifying the gaps and introducing the capabilities, avoidance of reworking seem necessary. Therefore, after reviewing the  literature we will discuss about meaning, overlapping to the other meanings, components, steps, advantages, challenges, the types of frameworks and their applications in healthcare sector. This study is based on search of databases (Proquest, PubMed, Google Scholar, Scence Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID)). This investigation has done with the websites and the specialized books with standard key words. After a careful study, 56 sources were selected and used in edition of final article. The results of this research can help the researchers to do the new research and understand the important concepts of that, thus it can be useful in designing and researching projects for researchers and health care providers as well.

    Keywords: Medical informatics, Software engineering, Health care, Framework, Dimensions
  • Anthony Ekpo*, Waheed Yahya Pages 226-235
    Background and aim

    In this paper, we present results regarding the outcomes of some anthropometric, epidemiological and demographic factors on the nutritional status of the under-five children which were categorized into three ordinal groups of Severe Acute Malnutrition (SAM), Moderate Acute Malnutrition (MAM) and Global Acute Malnutrition (GAM) in Kazaure Local Government Area in Nigeria.

    Methods

    An ordinal logistic model that depicted the log-odds in favour of GAM (normal) child was fitted to the data based on surveillance indexed by Weight-For-Height (WFH).

    Results

    The results showed that the proportional odd of measuring the nutritional status of a child in a nutrition survey using the WFH index has the OR= 7.43 (95% CI, 4.717 to 11.705) times greater, with Wald )1(2  =74.81, p<0.001, hence a statistically significant effect.

    Conclusion

    Based on the results and summary of findings, it can be concluded that age is a major predictor of the nutrition status of a child in a nutritional study when the surveillance is based on WFH index unlike sex and measles that do not play a major role.

    Keywords: Under-five, Statistical surveillance, Anthropometrics, Bilateral edema, Odd-ratio, Nutritional status, log-odds
  • Mohammad Khajeh, Masoud Mirzaei*, Azadeh Nadjarzadeh Pages 236-245
    Background and Aim

    Over the past few decades, different epidemiological studies have been conducted on the relationship between mental disorders and hypertension. However, conflicting results have been reported. This research aimed to evaluate the relationship between symptoms of depression, anxiety and stress with hypertension in a large population.

    Materials and Methods

    This cross-sectional analytic study was conducted using the results of in Yazd Health Study, Iran (N=9340). In addition, DASS-21 questionnaire was asked from the participants to assess depression, anxiety, and stress. Moreover, logistic regression was used to evaluate the relationship between symptoms of depression, anxiety and stress with hypertension.

    Results

    A negative association was observed between systolic and diastolic blood pressure and symptoms of depression, anxiety, and stress, which were independent from other variables. Regarding systolic blood pressure, a significant and reverse relationship was found in individuals with moderate stress (OR: 0.81, 95% CI: 0.69-0.95) and mild depression (OR: 0.82, 95% CI: 0.68-0.99). In terms of diastolic blood pressure, subjects with moderate stress had a lower blood pressure, compared to healthy individuals (OR: 0.86, 95% CI: 0.750.99). Furthermore, participants with depression had a lower chance of being diagnosed with hypertension, compared to healthy individuals.

    Conclusion

    The present research did not confirm the previous assumptions about the relationship between depression, anxiety and stress with hypertension. Our findings showed that symptoms of depression, anxiety, and stress are correlated with a low blood pressure.

    Keywords: Hypertension, Depression, Anxiety, Stress
  • Vajiheh Zarei, Seyyed Jamaluddin Tabibi*, Mahmoud Mahmoudi, Leila Riahi Pages 246-258
    Introduction

    Nowadays, the quality of services, especially in high volume clients, such as financial and care services, has become increasingly important. Therefore, quality of service in accordance with professional standards and customer expectations is important and a first step for it is a quality improvement.

    Objective

    The purpose of this study was to design a quality management model for providing health care in Iran.

    Method

    In this study, the comparative method was used to evaluate the health care quality indicators in selected countries (America-England-Japan-Malaysia-Egypt) and to compare their health care strategies. Hospital managers and people responsible for improving hospital quality in Iran have been involved in this research (377 questionnaire were analyzed). The study lasted from September 2018 to September 2019. Maxqda software was used to classify the adaptive variables. Maxqda software was used to classify the adaptive variables. LISREL software were used- Exploratory and confirmatory factor analysis- to identify the dimensions and validation of the mode .

    Results

    Twenty-four types of health care variables were identified from 6 countries. Exploratory factor analysis and questionnaire resulted in four general criteri: Quality Assurance, Quality Planning, Quality Control and Quality Improvement. Confirmatory factor analysis also showed that the identified dimensions are valid .

    Conclusion

    Considering that guarantee,control, planning and quality improvement have the highest impact respectively, continuous planning at the level of hospitals can lead to a significant increase in the quality of health care delivery .

    Keywords: Quality management, Health services, Quality assurance, Quality planning, Quality control, Quality improvement